SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database.
Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.
Predicting building collapse due to seismic motion is critical in design and more so after a major event. Damaged structures can appear sound, but collapse under following major events. There can thus be significant risk in decision making after a major seismic event concerning the safe occupation of a building or surrounding areas, versus the unknown impact of unknown major aftershocks. Model-based pushover analyses are effective if the structural properties are well understood, which is not valid post-event when this risk information is most useful. This research combines Hysteresis Loop Analysis (HLA) structural health monitoring (SHM) and Incremental Dynamic Analysis (IDA) methods to determine collapse capacity and probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. The nonlinear dynamic analysis method presented enables constant updating of building performance predictions using post-event SHM results. The resulting combined methods provide near real-time updating of collapse fragility curves as events progress, quantifying the change of collapse probability or seismic induced losses for decision-making - a novel, higher resolution risk analysis than previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model. Results show significant potential benefits and a clear evolution of risk. They also show clear need for extending SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010-2011 had significant post-event aftershocks after each main event. Finally, the overall method is generalisable to any typical engineering demand parameter.
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Prediction of building collapse due to significant seismic motion is a principle objective of earthquake engineers, particularly after a major seismic event when the structure is damaged and decisions may need to be made rapidly concerning the safe occupation of a building or surrounding areas. Traditional model-based pushover analyses are effective, but only if the structural properties are well understood, which is not the case after an event when that information is most useful. This paper combines hysteresis loop analysis (HLA) structural health monitoring (SHM) and incremental dynamic analysis (IDA) methods to identify and then analyse collapse capacity and the probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. This nonlinear dynamic analysis enables constant updating of building performance predictions following a given and subsequent earthquake events, which can result in difficult to identify deterioration of structural components and their resulting capacity, all of which is far more difficult using static pushover analysis. The combined methods and analysis provide near real-time updating of the collapse fragility curves as events progress, thus quantifying the change of collapse probability or seismic induced losses very soon after an earthquake for decision-making. Thus, this combination of methods enables a novel, higher-resolution analysis of risk that was not previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model, thus providing a relatively simpler means of assessing collapse probability immediately post-event when such speed can provide better information for critical decision-making. Finally, the results also show a clear need to extend the area of SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010–2011 had significant post-event aftershocks.
Prognostic modelling provides an efficient means to analyse the coastal environment and provide effective knowledge for long term urban planning. This paper outlines how the use of SWAN and Xbeach numerical models within the ESRI ArcGIS interface can simulate geomorphological evolution through hydrodynamic forcing for the Greater Christchurch coastal environment. This research followed the data integration techniques of Silva and Taborda (2012) and utilises their beach morphological modelling tool (BeachMM tool). The statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 were examined to determine whether these requirements are currently being complied with when applying the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013), and it would appear that it does not meet those requirements. This is because coastal hazard risk has not been thoroughly quantified by the installation of the Canterbury Earthquake Recovery Authority (CERA) residential red zone. However, the Christchurch City Council’s (CCC) flood management area does provide an extent to which managed coastal retreat is a real option. This research assessed the effectiveness of the prognostic models, forecasted a coastline for 100 years from now, and simulated the physical effects of extreme events such as storm surge given these future predictions. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon similar to the CCC’s flood management area. There are complex interactions at the Waimakariri River mouth with very high rates of accretion and erosion within a small spatial scale due to the river discharge. There is domination of the marine environment over the river system determined by the lack of generation of a distinct river delta, and river channel has not formed within the intertidal zone clearly. The Avon-Heathcote ebb tidal delta aggrades on the innner fan and erodes on the outer fan due to wave domination. The BeachMM tool facilitates the role of spatial and temporal analysis effectively and the efficiency of that performance is determined by the computational operating system.
Deformational properties of soil, in terms of modulus and damping, exert a great influence on seismic response of soil sites. However, these properties for sands containing some portion of fines particles have not been systematically addressed. In addition, simultaneous modelling of the modulus and damping behaviour of soils during cyclic loading is desirable. This study presents an experimental and computational investigation into the deformational properties of sands containing fines content in the context of site response analysis. The experimental investigation is carried on sandy soils sourced from Christchurch, New Zealand using a dynamic triaxial apparatus while the computational aspect is based on the framework of total-stress one-dimensional (1D) cyclic behaviour of soil. The experimental investigation focused on a systematic study on the deformational behaviour of sand with different amounts of fines content (particle diameter ≤ 75µm) under drained conditions. The silty sands were prepared by mixing clean sand with three different percentages of fines content. A series of bender element tests at small-strain range and stress-controlled dynamic triaxial tests at medium to high-strain ranges were conducted on samples of clean sand and silty sand. This allowed measurements of linear and nonlinear deformational properties of the same specimen for a wide strain range. The testing program was designed to quantify the effects of void ratio and fines content on the low-strain stiffness of the silty sand as well as on the nonlinear stress-strain relationship and corresponding shear modulus and damping properties as a function of cyclic shear strains. Shear wave velocity, Vs, and maximum shear modulus, Gmax, of silty sand was shown to be significantly smaller than the respective values for clean sands measured at the same void ratio, e, or same relative density, Dr. However, the test results showed that the difference in the level of nonlinearity between clean sand and silty sands was small. For loose samples prepared at an identical relative density, the behaviour of clean sand was slightly less nonlinear as compared to sandy soils with higher fines content. This difference in the nonlinear behaviour of clean sand and sandy soils was negligible for dense soils. Furthermore, no systematic influence of fines content on the material damping curve was observed for sands with fines content FC = 0 to 30%. In order to normalize the effects of fines on moduli of sands, equivalent granular void ratio, e*, was employed. This was done through quantifying the participation of fines content in the force transfer chain of the sand matrix. As such, a unified framework for modelling of the variability of shear wave velocity, Vs, (or shear modulus, Gmax) with void ratio was achieved for clean sands and sands with fines, irrespective of their fines content. Furthermore, modelling of the cyclic stress-strain behaviour based on this experimental program was investigated. The modelling effort focused on developing a simple constitutive model which simultaneously models the soil modulus and damping relationships with shear strains observed in laboratory tests. The backbone curve of the cyclic model was adopted based on a modified version of Kondner and Zelasko (MKZ) hyperbolic function, with a curvature coefficient, a. In order to simulate the hysteretic cycles, the conventional Masing rules (Pyke 1979) were revised. The parameter n, in the Masing’s criteria was assumed to be a function of material damping, h, measured in the laboratory. As such the modulus and damping produced by the numerical model could match the stress-strain behaviour observed in the laboratory over the course of this study. It was shown that the Masing parameter n, is strain-dependent and generally takes values of n ≤ 2. The model was then verified through element test simulations under different cyclic loadings. It was shown that the model could accurately simulate the modulus and the damping simultaneously. The model was then incorporated within the OpenSees computational platform and was used to scrutinize the effects of damping on one-dimensional seismic site response analysis. For this purpose, several strong motion stations which recorded the Canterbury earthquake sequence were selected. The soil profiles were modelled as semi-infinite horizontally layered deposits overlying a uniform half-space subjected to vertically propagating shear waves. The advantages and limitations of the nonlinear model in terms of simulating soil nonlinearity and associated material damping were further scrutinized. It was shown that generally, the conventional Masing criteria unconservatively may underestimate some response parameters such as spectral accelerations. This was shown to be due to larger hysteretic damping modelled by using conventional Masing criteria. In addition, maximum shear strains within the soil profiles were also computed smaller in comparison to the values calculated by the proposed model. Further analyses were performed to study the simulation of backbone curve beyond the strain ranges addressed in the experimental phase of this study. A key issue that was identified was that relying only on the modulus reduction curves to simulate the stress-strain behaviour of soil may not capture the actual soil strength at larger strains. Hence, strength properties of the soil layer should also be incorporated to accurately simulate the backbone curve.
The last seven years have seen southern New Zealand a ected by several large and damaging earthquakes: the moment magnitude (MW) 7.8 Dusky Sound earthquake on 15 July 2009, the MW 7.1 Dar eld (Canterbury) earthquake on 4 September 2010, and most notably the MW 6.2 Christchurch earthquake on 22 February 2011 and the protracted aftershock sequence. In this thesis, we address the postseismic displacement produced by these earthquakes using methods of satellite-based geodetic measurement, known as Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS), and computational modelling. We observe several ground displacement features in the Canterbury and Fiordland regions during three periods: 1) Following the Dusky Sound earthquake; 2) Following the Dar eld earthquake and prior to the Christchurch earthquake; and 3) Following the Christchurch earthquake until February 2015. The ground displacement associated with postseismic motion following the Dusky Sound earthquake has been measured by continuous and campaign GPS data acquired in August 2009, in conjunction with Di erential Interferometric Synthetic Aperture Radar (DInSAR) observations. We use an afterslip model, estimated by temporal inversion of geodetic data, with combined viscoelastic rebound model to account for the observed spatio-temporal patterns of displacement. The two postseismic processes together induce a signi cant displacement corresponding to principal extensional and contractual strain rates of the order of 10⁻⁷ and 10⁻⁸ yr⁻¹ respectively, across most of the southern South Island. We also analyse observed postseismic displacement following the Dusky Sound earthquake using a new inversion approach in order to describe afterslip in an elasticviscoelastic medium. We develop a mathematical framework, namely the "Iterative Decoupling of Afterslip and Viscoelastic rebound (IDAV)" method, with which to invert temporally dense and spatially sparse geodetic observations. We examine the IDAV method using both numerical and analytical simulations of Green's functions. For the post-Dar eld time interval, postseismic signals are measured within approximately one month of the mainshock. The dataset used for the post-Dar eld displacement spans the region surrounding previously unrecognised faults that ruptured during the mainshock. Poroelastic rebound in a multi-layered half-space and dilatancy recovery at shallow depths provide a satisfactory t with the observations. For the post-Christchurch interval, campaign GPS data acquired in February 2012 to February 2015 in four successive epochs and 66 TerraSAR-X (TSX) SAR acquisitions in descending orbits between March 2011 and May 2014 reveal approximately three years of postseismic displacement. We detect movement away from the satellite of ~ 3 mm/yr in Christchurch and a gradient of displacement of ~ 4 mm/yr across a lineament extending from the westernmost end of the Western Christchurch Fault towards the eastern end of the Greendale East Fault. The postseismic signals following the Christchurch earthquake are mainly accounted for by afterslip models on the subsurface lineament and nearby faults.
